| 43 | 0 | 30 |
| 下载次数 | 被引频次 | 阅读次数 |
目的 通过整合代谢组学与转录组学分析，探讨食管鳞状细胞癌（ESCC）淋巴结转移的代谢特征及相关分子机制。方法 选取30例ESCC患者血液样本，分为无淋巴结转移组（15例）和有淋巴结转移组（15例），进行液相色谱-质谱联用（LC-MS）非靶向代谢组学分析。通过质量控制（QC）样品监控数据稳定性，经XCMS预处理和CAMERA注释后获得代谢物数据矩阵。结合ESCC转录组数据集（GSE118493），利用limma筛选差异表达基因，并进行KEGG通路富集分析。基于代谢组与转录组结果，通过MetaboAnalyst构建代谢物-基因互作网络，并利用GEPIA2验证关键基因表达。进一步在KYSE-150细胞中通过siRNA沉默目标基因，采用实时荧光定量PCR（qPCR）、Westernblot验证沉默效率，并通过CCK-8、Transwell实验评估其对增殖、迁移与侵袭的影响。结果 比较伴有与不伴有淋巴结转移的ESCC患者的临床基线特征，差异无统计学意义。代谢组学分析显示两组血清代谢谱存在显著分离，鉴定出大量差异代谢物，并富集于癌症相关通路。进一步筛选出数种关键代谢物，其诊断效能良好[受试者工作特征曲线下面积（AUC）>0.80]。进一步整合转录组学数据分析显示，差异代谢物α-亚麻酸与FADS1基因密切相关，且脂肪酸去饱和酶1（FADS1）在ESCC肿瘤组织中表达显著上调。体外功能实验证实，沉默FADS1可显著抑制KYSE-150细胞的增殖、迁移及侵袭能力。结论 ESCC淋巴结转移患者血清代谢谱显著改变，FADS1基因上调促进癌细胞增殖、迁移与侵袭，是ESCC潜在的诊断标志物和治疗靶点。
Abstract：Objective To investigate the metabolic characteristics and associated molecular mechanisms underlying lymph node metastasis in esophageal squamous cell carcinoma (ESCC) by integrating metabolomics and transcriptomics analyses. Methods Blood samples were collected from 30 ESCC patients， and divided into two groups: non-lymph node metastasis group (n=15) and lymph node metastasis group (n=15). Non-targeted metabolomics analysis was performed using liquid chromatography-mass spectrometry (LC-MS). Data stability was monitored using quality control (QC) samples. After XCMS preprocessing and CAMERA annotation， a metabolite data matrix was obtained. Combined with the ESCC transcriptomics dataset (GSE118493)， differentially expressed genes were screened using limma， followed by KEGG pathway enrichment analysis. Based on the metabolomics and transcriptomics results， a metabolite–gene interaction network was constructed using MetaboAnalyst， and key gene expression was validated using GEPIA2. Subsequently， the target gene was silenced by siRNA in KYSE-150 cells. Silencing efficiency was verified by quantitative real-time PCR (qPCR) and Western blot. The effects on proliferation， migration， and invasion were assessed using Cell Counting Kit-8 (CCK-8)， wound healing， and Transwell assays. Results No statistically significant differences in baseline clinical characteristics were observed between ESCC patients with and without lymph node metastasis. Metabolomics analysis revealed a clear separation in serum metabolic profiles between the two groups， with a large number of differential metabolites identified， which were enriched in cancer-related pathways. Several key metabolites were screened out， demonstrating good diagnostic performance (area under the receiver operating characteristic curve(AUC) > 0.80). Integrated transcriptomics analysis further showed that the differential metabolite α-linolenic acid was closely associated with the FADS1 gene， and FADS1 expression was significantly upregulated in ESCC tumor tissues. In vitro functional experiments confirmed that silencing fatty acid desaturase 1(FADS1) significantly inhibited the proliferation， migration， and invasion of KYSE-150 cells. Conclusion This study reveals significant alterations in serum metabolic profiles of ESCC patients with lymph node metastasis and identifies metabolites with diagnostic potential. Upregulation of the FADS1 gene promotes cancer cell proliferation， migration， and invasion， making it a potential diagnostic biomarker and therapeutic target for ESCC.
[1] 周 菲， 史志周， 商 利， 等. 食管鳞癌中SHANK2基因断裂及其临床意义[J]. 安徽医科大学学报， 2017， 52(10): 1545-9.
[1] Zhou F， Shi Z Z， Shang L， et al. Clinical relevance of SHANK2 splitting in esophageal squamous cell carcinoma[J]. Acta Univ Med Anhui， 2017， 52(10): 1545-9.
[2] Zhu H， Fan X， Liu C， et al. Immune cellular patterns predicting lymph node status helps personalized management of stage T1 esophageal squamous cell carcinoma[J]. Mod Pathol， 2025， 38(10): 100814. doi:10.1016/j.modpat.2025.100814.
[3] Chen J， Zhang J， Zhu Y， et al. Focal adhesion kinase/Src family kinase axis-mediated tyrosine phosphorylation of metabolic enzymes facilitates tumor metastasis[J]. Signal Transduct Target Ther， 2025， 10: 280. doi:10.1038/s41392-025-02395-5.
[4] Sun Y， Liu W， Su M， et al. Purine salvage-associated metabolites as biomarkers for early diagnosis of esophageal squamous cell carcinoma: a diagnostic model-based study[J]. Cell Death Discov， 2024， 10(1): 139. doi:10.1038/s41420-024-01896-6.
[5] Chen Z， Huang X， Gao Y， et al. Plasma-metabolite-based machine learning is a promising diagnostic approach for esophageal squamous cell carcinoma investigation[J]. J Pharm Anal， 2021， 11(4): 505-14. doi:10.1016/j.jpha.2020.11.009.
[6] Zhang L， Zhu L J， Zhao Y， et al. STING inhibits the progression of esophageal squamous cell carcinoma by suppressing CPT1A-mediated fatty acid β-oxidation[J]. Acta Pharmacol Sin， 2025， 46(10): 2793-807. doi:10.1038/s41401-025-01581-z.
[7] Heravi G， Liu Z， Herroon M， et al. Targeting polyunsaturated fatty acids desaturase FADS1 inhibits renal cancer growth via ATF3-mediated ER stress response[J]. Biomed Pharmacother， 2025， 186: 118006. doi:10.1016/j.biopha.2025.118006.
[8] Zang Q， Sun C， Chu X， et al. Spatially resolved metabolomics combined with multicellular tumor spheroids to discover cancer tissue relevant metabolic signatures[J]. Anal Chim Acta， 2021， 1155: 338342. doi:10.1016/j.aca.2021.338342.
[9] Jiao R， Jiang W， Xu K， et al. Lipid metabolism analysis in esophageal cancer and associated drug discovery[J]. J Pharm Anal， 2024， 14(1): 1-15. doi:10.1016/j.jpha.2023.08.019.
[10] Liu X， Hong R， Du P， et al. The metabolic genomic atlas reveals potential drivers and clinically relevant insights into the etiology of esophageal squamous cell carcinoma[J]. Theranostics， 2022， 12(14): 6160-78. doi:10.7150/thno.70814.
[11] Yin Y， Wang Y， Yu X， et al. Spatial isoforms reveal the mechanisms of metastasis[J]. Adv Sci， 2024， 11(43): 2402242. doi:10.1002/advs.202402242.
[12] Jia Y， Zhang B， Zhang C， et al. Single-cell transcriptomic analysis of primary and metastatic tumor ecosystems in esophageal squamous cell carcinoma[J]. Adv Sci， 2023， 10(7): 2204565. doi:10.1002/advs.202204565.
[13] Gao Y， He S， Meng X， et al. Multi-omics analysis reveals immunosuppression in oesophageal squamous cell carcinoma induced by creatine accumulation and HK3 deficiency[J]. Genome Med， 2025， 17(1): 44. doi:10.1186/s13073-025-01465-1.
[14] Shen X， Zhang Y， Wang Q， et al. Comprehensive metabolic profiling uncovers early variation and biomarkers of esophageal squamous cell carcinoma[J]. Sci China Life Sci， 2026， 69(3): 881-95. doi:10.1007/s11427-025-3082-9.
基本信息:
中图分类号:R735.1
引用信息:
[1]陈克功,冀林,徐瀚卿,等.基于代谢组学解析食管鳞癌淋巴结转移的代谢特征与潜在机制[J].安徽医科大学学报().
基金信息:
安徽省高等学校科研计划项目（编号：2022AH051185）; 安徽省卫生健康科研项目（编号：AHWJ2024Aa30095）; 安徽省博士后科研项目（编号：2024B784）; 中国博士后科学基金面上项目（编号：2023M740027）; 中国国家留学基金项目（编号：202508340076）
2026-08-27
2026-08-27
2026-08-27